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Dong Chen

Schmidt AI in Science Postdoctoral Fellow at Cornell University

• Contact: dc2339@cornell.edu
• Office: Olin Hall, Room 318, 113 Ho Plaza, Ithaca, NY 14853
I am on the job market this cycle and would be grateful for any opportunities to connect.

Bios

Starting in 2026, I will join Cornell University as a Schmidt AI in Science Postdoctoral fellow in the R.F. Smith School of Chemical and Biomolecular Engineering, working with Prof. Fengqi You and continuing my research in AI for Science. Before joining Cornell, I was a Visiting Assistant Professor in the Department of Mathematics at Michigan State University, working with Prof. Guo-Wei Wei in East Lansing, Michigan. I earned my Ph.D. in Materials Physics and Chemistry from Peking University in 2022 under the supervision of Prof. Feng Pan.

Research Interests: My research centers on AI for Science, combining mathematical modeling and machine learning (ML) to advance discovery in chemistry, materials, and biology. I develop methods in topological data analysis (TDA), representation learning, and foundation models, with applications to drug discovery, drug resistance, addiction research, and the discovery of energy storage, and porous materials.

Awards & Grants

2025–2029 U.S. Department of Energy, Microelectronics science research center projects for energy efficiency and extreme environments, $480,000 (Co-PI).
2024–2026 American Mathematical Society, AMS Simons Travel Grant, $5,000 (Recipient).
2023–2024 Bristol Myers Squibb, Virtual patient simulation and analysis for BMS' heart failure model and myosin, $371,000 (Co-PI).

News

Aug 25, 2026 I accepted an Associate Editor appointment for the In silico Methods and Artificial Intelligence for Drug Discovery section of Frontiers in Drug Discovery.
Aug 21, 2026 Publication of "Interaction topology theory deciphers multiscale codes of MOF-like materials" in Science Advances.
Aug 20, 2026 Starting in 2026, I will join Cornell University as a Postdoctoral Associate in the R.F. Smith School of Chemical and Biomolecular Engineering, working with Prof. Fengqi You on AI for Science.
Aug 17, 2025 Presentation at the COMP: Division of Computers in Chemistry - SESSION: Machine Learning in Chemistry, ACS Fall 2025

Selected Publications

  1. Nat. Mach. Intell.
    Multiscale topology-enabled structure-to-sequence transformer for protein–ligand interaction predictions
    Dong Chen, Jian Liu, and Guo-Wei Wei
    Nature Machine Intelligence, 2024
  2. Nat. Commun.
    Algebraic graph-assisted bidirectional transformers for molecular property prediction
    Dong Chen, Kaifu Gao, Duc Duy Nguyen, Xin Chen, Yi Jiang, Guo-Wei Wei, and Feng Pan
    Nature Communications, 2021
  3. Sci. Adv.
    Interaction topology theory deciphers multiscale codes of MOF-like materials
    Dong Chen, Jian Liu, Chun-Long Chen, and Guo-Wei Wei
    Science Advances, 2026
  4. JACS
    Superionic Ionic Conductor Discovery via Multiscale Topological Learning
    Dong Chen, Bingxu Wang, Shunning Li, Wentao Zhang, Kai Yang, Yongli Song, Guo-Wei Wei, and Feng Pan
    Journal of the American Chemical Society, 2025
  5. Adv. Sci.
    Drug Resistance Predictions Based on a Directed Flag Transformer
    Dong Chen, Gengzhuo Liu, Hongyan Du, Benjamin Jones, Junjie Wee, Rui Wang, Jiahui Chen, Jana Shen, and Guo-Wei Wei
    Advanced Science, 2024
  6. JPCL
    Path topology in molecular and materials sciences
    Dong Chen, Jian Liu, Jie Wu, Guo-Wei Wei, Feng Pan, and Shing-Tung Yau
    The Journal of Physical Chemistry Letters, 2023